Although a wealth of product information is available to users online, it can often be difficult for users to quickly and effectively discover and explore related products and/or competing products that they should consider as part of their shopping experience. This is especially true when a user is looking to explore a product category unfamiliar to the user and the user may wish to better understand the options that are available before making a purchase decision.
Currently, if a user does not know the particular product he/she is interested in, the user can search for the product class (such as ‘digital camera’) on the web using a search engine. The user will see a list of web search results which are textually most ‘relevant’ to the words ‘digital camera” and/or a list of digital camera offers aggregated from various e-commerce sites. However, the user cannot see a summary view which categorizes relevant digital cameras into brands, product lines, or feature sets easily. Additionally, for web search results, the search engine often returns a large number of documents or web pages. The user is then left to sift through the list of documents, links, and associated information to find desired information. This process can be cumbersome, frustrating, and time consuming for the user.
Alternatively, if the user has a target product in mind, the user can start by searching for that particular product name. For instance, the user may employ a shopping search engine to find some description, reviews and offers information about the product scattered across a number of web sites. However, there exists no effective and consistent way for the user to discover comparable products across brands, product lines, and price classes that they should consider as an alternative.
The user may also go to a general shopping site and browse through the relevant products under the category they are interested in to read more information about that category of products. The problem with this approach is that the useful grouping of products is presented in a traditional browse hierarchy and requires a fair amount of navigating through the site structure before the user can comprehend the holistic groupings, i.e., the inter-relationship of products within a product class.
As a further alternative, the user may employ a niche site specializing in a certain product class and learn about all the various product models. The obvious problem with this is that the user is assumed to have prior knowledge of which is the authoritative or trusted site specializing in a particular product class. However, that assumption does not hold when a user was not an expert in that area to begin with. Secondly, building these expert sites requires a significant amount of editorial effort and expert knowledge to maintain its quality and freshness.
In some instances, the user can find a comparable product or other related product recommendation from general shopping sites when they're researching about a certain product. A general shopping site providing such relationship information typically only collects and summarizes data based on the behavior of their own users, so it is not representative of the entire Internet and therefore the entire market. Additionally, the recommendations are typically in a form of a flat list with no notion of the relationships between brand lines, quality, comparable products, etc.